The regulation of fat metabolism during aerobic exercise

Since the lipid profile is altered by physical activity, the study of lipid metabolism is a remarkable element in understanding if and how physical activity affects the health of both professional athletes and sedentary subjects. Although not fully defined, it has become clear that resistance exercise uses fat as an energy source. The fatty acid oxidation rate is the result of the following processes: (a) triglycerides lipolysis, most abundant in fat adipocytes and intramuscular triacylglycerol (IMTG) stores, (b) fatty acid transport from blood plasma to muscle sarcoplasm, (c) availability and hydrolysis rate of intramuscular triglycerides, and (d) transport of fatty acids through the mitochondrial membrane. In this review, we report some studies concerning the relationship between exercise and the aforementioned processes also in light of hormonal controls and molecular regulations within fat and skeletal muscle cells

Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies

The year 2020 saw the covid-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world have been faced with the challenge of protecting public health while keeping the economy running to the greatest extent possible. Epidemiological models provide insight into the spread of these types of diseases and predict the e_ects of possible intervention policies. However, to date, even the most data-driven intervention policies rely on heuristics. In this paper, we study how reinforcement learning (RL) and Bayesian inference can be used to optimize mitigation policies that minimize economic impact without overwhelming hospital capacity. Our main contributions are (1) a novel agent-based pandemic simulator which, unlike traditional models, is able to model _ne-grained interactions among people at speci_c locations in a community; (2) an RL- based methodology for optimizing _ne-grained mitigation policies within this simulator; and (3) a Hidden Markov Model for predicting infected individuals based on partial observations regarding test results, presence of symptoms, and past physical contacts

Physical exercise in major depression: Reducing the mortality gap while improving clinical outcomes

Major depression shortens life while the effectiveness of frontline treatments remains modest. Exercise has been shown to be effective both in reducing mortality and in treating symptoms of major depression, but it is still underutilized in clinical practice, possibly due to prevalent misperceptions. For instance, a common misperception is that exercise is beneficial for depression mostly because of its positive effects on the body (\u201cfrom the neck down\u201d), whereas its effectiveness in treating core features of depression (\u201cfrom the neck up\u201d) is underappreciated. Other long-held misperceptions are that patients suffering from depression will not engage in exercise even if physicians prescribe it, and that only vigorous exercise is effective. Lastly, a false assumption is that exercise may be more harmful than beneficial in old age, and therefore should only be recommended to younger patients. This narrative review summarizes relevant literature to address the aforementioned misperceptions and to provide practical recommendations for prescribing exercise to individuals with major depression

A novel compound of triphenyltin(IV) with N-tert-butoxycarbonyl-L-ornithine causes cancer cell death by inducing a p53-dependent activation of the mitochondrial pathway of apoptosis

The triphenyltin(IV) compound with N-tert-butoxycarbonyl-L-ornithine (Boc-Orn-OH), [Ph3Sn(Boc-Orn-O)], was synthesized and characterized by elemental analysis, FT-IR, solution1H,13C and119Sn NMR and ESI mass spectrometry. The organotin(IV) compound inhibited at very low micromolar concentrations the growth of human tumor cell lines HepG2 (hepatocarcinoma cells), MCF-7 (mammary cancer) and HCT116 (colorectal carcinoma) while it did not affect the viability of non-malignant human-derived hepatic cells Chang. The mechanism of the antiproliferative effect of Ph3Sn(Boc-Orn-O), investigated on human hepatoma HepG2 cells, was pro-apoptotic, being associated with externalization of plasma membrane phosphatidylserine, chromatin condensation or fragmentation and mitochondrial dysfunction as well as with increase of p53 levels.The triphenyltin(IV) compound with N-tert-butoxycarbonyl-L-ornithine (Boc-Orn-OH), [Ph3Sn(Boc-Orn-O)], was synthesized and characterized by elemental analysis, FT-IR, solution 1H, 13C and 119Sn NMR and ESI mass spectrometry. The organotin(IV) compound inhibited at very low micromolar concentrations the growth of human tumor cell lines HepG2 (hepatocarcinoma cells), MCF-7 (mammary cancer) and HCT116 (colorectal carcinoma) while it did not affect the viability of non-malignant human-derived hepatic cells Chang. The mechanism of the antiproliferative effect of Ph3Sn(Boc-Orn-O), investigated on human hepatoma HepG2 cells, was pro-apoptotic, being associated with externalization of plasma membrane phosphatidylserine, chromatin condensation or fragmentation and mitochondrial dysfunction as well as with increase of p53 levels

Probiotics improve the neurometabolic profile of rats with chronic cholestatic liver disease.

Chronic liver disease leads to neuropsychiatric complications called hepatic encephalopathy (HE). Current treatments have some limitations in their efficacy and tolerability, emphasizing the need for alternative therapies. Modulation of gut bacterial flora using probiotics is emerging as a therapeutic alternative. However, knowledge about how probiotics influence brain metabolite changes during HE is missing. In the present study, we combined the advantages of ultra-high field in vivo <sup>1</sup> H MRS with behavioural tests to analyse whether a long-term treatment with a multistrain probiotic mixture (VIVOMIXX) in a rat model of type C HE had a positive effect on behaviour and neurometabolic changes. We showed that the prophylactic administration of this probiotic formulation led to an increase in gut Bifidobacteria and attenuated changes in locomotor activity and neurometabolic profile in a rat model of type C HE. Both the performance in behavioural tests and the neurometabolic profile of BDL + probiotic rats were improved compared to the BDL group at week 8 post-BDL. They displayed a significantly lesser increase in brain Gln, a milder decrease in brain mIns and a smaller decrease in neurotransmitter Glu than untreated animals. The clinical implications of these findings are potentially far-reaching given that probiotics are generally safe and well-tolerated by patients

Luminosity- and morphology-dependent clustering of galaxies

How does the clustering of galaxies depend on their inner properties like morphological type and luminosity? We address this question in the mathematical framework of marked point processes and clarify the notion of luminosity and morphological segregation. A number of test quantities such as conditional mark-weighted two-point correlation functions are introduced. These descriptors allow for a scale-dependent analysis of luminosity and morphology segregation. Moreover, they break the degeneracy between an inhomogeneous fractal point set and actual present luminosity segregation. Using the Southern Sky Redshift Survey~2 (da Costa et al. 1998, SSRS2) we find both luminosity and morphological segregation at a high level of significance, confirming claims by previous works using these data (Benoist et al. 1996, Willmer et al. 1998). Specifically, the average luminosity and the fluctuations in the luminosity of pairs of galaxies are enhanced out to separations of 15Mpc/h. On scales smaller than 3Mpc/h the luminosities on galaxy pairs show a tight correlation. A comparison with the random-field model indicates that galaxy luminosities depend on the spatial distribution and galaxy-galaxy interactions. Early-type galaxies are also more strongly correlated, indicating morphological segregation. The galaxies in the PSCz catalog (Saunders et al. 2000) do not show significant luminosity segregation. This again illustrates that mainly early-type galaxies contribute to luminosity segregation. However, based on several independent investigations we show that the observed luminosity segregation can not be explained by the morphology-density relation alone.Comment: aastex, emulateapj5, 20 pages, 13 figures, several clarifying comments added, ApJ accepte

Bridging the future of cardiac stimulation: physiologic or leadless pacing?

Cardiac simulation has moved from early life-saving pacemakers meant only to prevent asystole to current devices capable of physiologic stimulation for the treatment of heart rhythm and heart failure, that are also intended for remote patient and disease-progression monitoring. The actual vision of contemporary pacing aims to correct the electrophysiologic roots of mechanical inefficiency regardless of underlying structural heart diseases. The awareness of the residual cardiac dyssynchrony related to customary cardiac pacing has changed the concept of what truly represents “physiologic pacing”. On a different perspective, leadless stimulation to abolish CIED surgery and prevent lead-related complications is becoming a priority both for young device recipients and for frail, elderly patients. Careful clinical evaluation attempts to bridge decision-making to patient-tailored therapy

Radial Velocity Studies of Close Binary Stars. IX

Radial-velocity measurements and sine-curve fits to the orbital velocity variations are presented for the eighth set of ten close binary systems: AB And, V402 Aur, V445 Cep, V2082 Cyg, BX Dra, V918 Her, V502 Oph, V1363 Ori, KP Peg, V335 Peg. Half of the systems (V445 Cep, V2082 Cyg, V918 Her, V1363 Ori, V335 Peg) were discovered photometrically by the Hipparcos mission and all systems are double-lined (SB2) contact binaries. The broadening function method permitted improvement of the orbital elements for AB And and V502 Oph. The other systems have been observed for radial velocity variations for the first time; in this group are five bright (V<7.5) binaries: V445 Cep, V2082 Cyg, V918 Her, KP Peg and V335 Peg. Several of the studied systems are prime candidates for combined light and radial-velocity synthesis solutions.Comment: 17+ pages, 2 tables, 4 figure

Detection and Classification of Hysteroscopic Images Using Deep Learning

Background: Although hysteroscopy with endometrial biopsy is the gold standard in the diagnosis of endometrial pathology, the gynecologist experience is crucial for a correct diagnosis. Deep learning (DL), as an artificial intelligence method, might help to overcome this limitation. Unfortunately, only preliminary findings are available, with the absence of studies evaluating the performance of DL models in identifying intrauterine lesions and the possible aid related to the inclusion of clinical factors in the model. Aim: To develop a DL model as an automated tool for detecting and classifying endometrial pathologies from hysteroscopic images. Methods: A monocentric observational retrospective cohort study was performed by reviewing clinical records, electronic databases, and stored videos of hysteroscopies from consecutive patients with pathologically confirmed intrauterine lesions at our Center from January 2021 to May 2021. Retrieved hysteroscopic images were used to build a DL model for the classification and identification of intracavitary uterine lesions with or without the aid of clinical factors. Study outcomes were DL model diagnostic metrics in the classification and identification of intracavitary uterine lesions with and without the aid of clinical factors. Results: We reviewed 1500 images from 266 patients: 186 patients had benign focal lesions, 25 benign diffuse lesions, and 55 preneoplastic/neoplastic lesions. For both the classification and identification tasks, the best performance was achieved with the aid of clinical factors, with an overall precision of 80.11%, recall of 80.11%, specificity of 90.06%, F1 score of 80.11%, and accuracy of 86.74 for the classification task, and overall detection of 85.82%, precision of 93.12%, recall of 91.63%, and an F1 score of 92.37% for the identification task. Conclusion: Our DL model achieved a low diagnostic performance in the detection and classification of intracavitary uterine lesions from hysteroscopic images. Although the best diagnostic performance was obtained with the aid of clinical data, such an improvement was slight

Mark correlations: relating physical properties to spatial distributions

Mark correlations provide a systematic approach to look at objects both distributed in space and bearing intrinsic information, for instance on physical properties. The interplay of the objects' properties (marks) with the spatial clustering is of vivid interest for many applications; are, e.g., galaxies with high luminosities more strongly clustered than dim ones? Do neighbored pores in a sandstone have similar sizes? How does the shape of impact craters on a planet depend on the geological surface properties? In this article, we give an introduction into the appropriate mathematical framework to deal with such questions, i.e. the theory of marked point processes. After having clarified the notion of segregation effects, we define universal test quantities applicable to realizations of a marked point processes. We show their power using concrete data sets in analyzing the luminosity-dependence of the galaxy clustering, the alignment of dark matter halos in gravitational $N$-body simulations, the morphology- and diameter-dependence of the Martian crater distribution and the size correlations of pores in sandstone. In order to understand our data in more detail, we discuss the Boolean depletion model, the random field model and the Cox random field model. The first model describes depletion effects in the distribution of Martian craters and pores in sandstone, whereas the last one accounts at least qualitatively for the observed luminosity-dependence of the galaxy clustering.Comment: 35 pages, 12 figures. to be published in Lecture Notes of Physics, second Wuppertal conference "Spatial statistics and statistical physics